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Genetic Diversity and Population Structure of Leishmania infantum from Southeastern France: Evaluation Using Multi-Locus Microsatellite Typing

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HAL Id: hal-01881676

https://hal.archives-ouvertes.fr/hal-01881676

Submitted on 5 Oct 2018

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Francine Pratlong, Benoit Faucher, Fakhri Jeddi, Sandy Moore, Gregory Michel, Srikanth Aluru, et al.

To cite this version:

Christelle Pomares, Pierre Marty, Anne Laure Bañuls, Emmanuel Lemichez, Francine Pratlong, et al..

Genetic Diversity and Population Structure of Leishmania infantum from Southeastern France: Eval-

uation Using Multi-Locus Microsatellite Typing. PLoS Neglected Tropical Diseases, Public Library

of Science, 2016, 10 (1), pp.e0004303. �10.1371/journal.pntd.0004303�. �hal-01881676�

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Microsatellite Typing

Christelle Pomares1,2,3*, Pierre Marty1,2,3, Anne Laure Bañuls4, Emmanuel Lemichez1, Francine Pratlong4,5, Benoît Faucher6, Fakhri Jeddi7, Sandy Moore7, Grégory Michel1, Srikanth Aluru1,8, Renaud Piarroux7, Mallorie Hide4

1INSERM, U1065, Centre Méditerranéen de Médecine Moléculaire, C3M, Toxines Microbiennes dans la Relation Hôte–Pathogènes, Nice, France,2Université de Nice Sophia Antipolis, Faculté de Médecine, Nice, France,3Parasitologie-Mycologie, Centre Hospitalier Universitaire l’Archet, CS 23079 06202, Nice, France, 4UMR MIVEGEC IRD 224-CNRS 5290-Université Montpellier, Montpellier, France,5Département de Parasitologie–Mycologie, CHRU de Montpellier, Centre National de Référence des Leishmanioses, Montpellier, France,6Service des Maladies Infectieuses, CHU Hôpital Nord, Assistance Publique-Hôpitaux de Marseille, Marseille, France,7Aix-Marseille Université, UMR MD3, Marseille, France,8Aix–Marseille Université, Marseille, France

‡These authors are joint last authors on this work.

*pomares.c@chu-nice.fr

Abstract

In the south of France, Leishmania infantum is responsible for numerous cases of canine leishmaniasis (CanL), sporadic cases of human visceral leishmaniasis (VL) and rare cases of cutaneous and muco-cutaneous leishmaniasis (CL and MCL, respectively). Several endemic areas have been clearly identified in the south of France including the Pyrénées- Orientales, Cévennes (CE), Provence (P), Alpes-Maritimes (AM) and Corsica (CO). Within these endemic areas, the two cities of Nice (AM) and Marseille (P), which are located 150 km apart, and their surroundings, concentrate the greatest number of French autochtho- nous leishmaniasis cases. In this study, 270 L. infantum isolates from an extended time period (1978 – 2011) from four endemic areas, AM, P, CE and CO, were assessed using Multi-Locus Microsatellite Typing (MLMT). MLMT revealed a total of 121 different genotypes with 91 unique genotypes and 30 repeated genotypes. Substantial genetic diversity was found with a strong genetic differentiation between the Leishmania populations from AM and P. However, exchanges were observed between these two endemic areas in which it seems that strains spread from AM to P. The genetic differentiations in these areas suggest strong epidemiological structuring. A model-based analysis using STRUCTURE revealed two main populations: population A (consisting of samples primarily from the P and AM endemic areas with MON-1 and non-MON-1 strains) and population B consisting of only MON-1 strains essentially from the AM endemic area. For four patients, we observed sev- eral isolates from different biological samples which provided insight into disease relapse and re-infection. These findings shed light on the transmission dynamics of parasites in

OPEN ACCESS

Citation:Pomares C, Marty P, Bañuls AL, Lemichez E, Pratlong F, Faucher B, et al. (2016) Genetic Diversity and Population Structure ofLeishmania infantumfrom Southeastern France: Evaluation Using Multi-Locus Microsatellite Typing. PLoS Negl Trop Dis 10(1): e0004303. doi:10.1371/journal.

pntd.0004303

Editor:Gabriele Schönian, Charité University Medicine Berlin, GERMANY

Received:June 30, 2015 Accepted:November 24, 2015 Published:January 25, 2016

Copyright:© 2016 Pomares et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability Statement:All relevant data are within the paper and its Supporting Information files.

Funding:SA received a grant from Infectiopôle Sud and Infectiopôle Sud provided some equipment used in this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests:The authors have declared that no competing interests exist.

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Author Summary

In the south of France, the parasite Leishmania infantum is responsible for diseases that primarily affect dogs but can also impact humans. Several endemic areas have been clearly identified in the south of France including the Pyrénées-Orientales, Cévennes (CE), Pro- vence (P), Alpes-Maritimes (AM) and Corsica (CO). In this study, 270 L. infantum isolates from four endemic areas, AM, P, CE and CO, were assessed using Multi-Locus Microsatel- lite Typing (MLMT), a tool applied for population genetic studies. MLMT revealed a strong genetic differentiation between the Leishmania populations from AM and P with exchanges observed between these two endemic areas. For four patients, the occurrence of disease relapses and re-infections was examined. These findings shed light on the trans- mission dynamics of parasites in humans. This study represents the most extensive popu- lation analysis of L. infantum isolates using MLMT conducted in France.

Introduction

Leishmaniases are a group of diseases caused by obligatory intracellular protozoan parasites of

the genus Leishmania. Among the species of Leishmania, Leishmania infantum is mostly

responsible for canine leishmaniasis (CanL), although it also causes sporadic cases of human

visceral leishmaniasis (VL), and rare cases of cutaneous and muco-cutaneous leishmaniasis

(CL and MCL) throughout the Mediterranean basin [1]. Transmission to humans is caused by

the bite of infected phlebotomine sandflies, and dogs are considered to be the principal domes-

tic reservoir. In France, the parasite is currently only endemic in the south of France, along the

Mediterranean coast, where several foci have been clearly identified: Pyrénées-Orientales,

Cévennes (CE), Provence (P), Alpes-Maritimes (AM) and Corsica (CO) [2]. In the Provence-

Alpes-Côtes d’Azur (PACA) region, which comprises the AM and P endemic areas, transmis-

sion has been reported for 100 years [3,4]. The two cities of Nice and Marseille, which are

located 150 km apart, and their surroundings concentrate the greatest number of French

autochthonous leishmaniasis cases [2,5]. Although the same species of L . infantum (primarily

zymodeme MON-1), the same predominant vector (Phlebotomus perniciosus) and the same

and unique reservoir (dog) are found in both regions, the transmission environment of VL is

heterogeneous in these two foci [5]. Disease transmission in Nice and the surrounding area is

associated with scattered habitation and mixed forest in the foothills [5]. In contrast, around

Marseille, VL transmission is associated with an urban environment [5]. Regarding the main

vector; Phlebotomus pernicious ; the population is quite homogeneous and belongs mainly to

the same haplogroup (for 88% pern01) in Provence, France [6]. The isolates of L. infantum

from AM and P endemic foci have been characterized using Multi-Locus Enzyme Electropho-

resis (MLEE), which is the current reference method. However, MLEE based analyses are lim-

ited at the intrinsic level of polymorphisms. Thus, differentiating between isolates in PACA

region is impossible using the MLEE method [7]. Epidemiological studies on L. infantum

require the use of highly discriminative techniques that can differentiate between MON-1

strains. Multi-Locus Microsatellite Typing (MLMT) has been shown to be a powerful tool for

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asymptomatic carrier and HIV+ populations [9]. However, due to the weak sample size, these results must be confirmed on a larger sample set [9].

In the current study, microsatellite markers were used to analyze the genetic diversity of L . infantum parasites from Southeast France, with a focus on the PACA region. We assessed an extensive panel of isolates from an extended time period (1978 – 2011), from the two endemic regions of AM and P. The geographical and temporal distributions of genotypes were exam- ined. The microsatellite profiles were used to assess relapse and re-infection among patients as well as the association between genotype and the various clinical forms of the disease.

Materials and Methods Parasites

The L. infantum isolates used in this study were obtained from the collection of the Centre National de Référence des Leishmania (Leishmania collection, BRC-Leish, Montpellier, France, BioBank N° BB-0033-00052). All human and animal samples had been isolated from patients and animals as part of routine diagnosis and treatment with no unnecessary invasive proce- dures. A total of 270 L . infantum isolates from the south of France were included in this study (Table 1). This panel included 247 human isolates from 239 patients (four patients harbored more than one isolate), 20 from CanL, one from feline leishmaniasis and two from sandflies.

Among the 239 patients, there were 154 adult VL cases, 58 infant VL cases, 13 CL cases (five infants, seven adults and one unknown), three MCL adult cases, nine asymptomatic carriers (in adults) and two unknown cases (one adult and one unknown). Among the 247 human sam- ples, 139 were isolated from immunocompetent patients, 95 from immunocompromised HIV + patients, 11 from immunocompromised patients other than HIV+ (e.g., renal transplanta- tion, lymphoma, auto immunity disease and cancer) and two from unknown cases. The loca- tion of isolates based on their position relative to the Vars River (S1 Table) was used for genetic differentiation analysis.

Concerning the geographical distribution (Fig 1), the samples were collected from the endemic areas of AM (n = 178), P (n = 75), CO (n = 9) and CE (n = 8). The samples were iso- lated at the University Hospitals of Nice, Marseille and Montpellier (France) between 1978 and 2011. MLEE typing and cryoconservation were performed at the Centre National de Référence des Leishmania (Leishmania collection, BRC-Leish, Montpellier, France, BioBank N° BB-0033- 00052). Overall, 259 isolates were characterized as zymodeme MON-1, six were MON-24, one was MON-11, one was MON-80 and one was MON-108. The data were unavailable for two isolates. For this study, the primary cultures from the patient stored at -80°C were thawed and the cells were cultured for six days before harvesting for DNA extraction.

DNA extraction

The microsatellite data indicated with an asterisk in Table 1 were obtained from a previous study [9].

DNA of the remaining isolates was extracted from promastigotes grown in Schneider’s

insect medium (Sigma Aldrich, France) supplemented with serum calf, urine, penicillin, strep-

tomycin and L-glutamine (Sigma Aldrich). Promastigotes were harvested on the sixth day of

culture, and DNA was extracted from a pellet of 2X10

8

parasites using a QIAamp DNA mini

kit (Qiagen, France) according to the manufacturer’s instructions. DNA extracted from the

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P Patient 1 MHOM/FR/94/LPM135 1994 VL HIV MON-1 1 A 6 3

AM Patient 2 MHOM/FR/90/LPN63 1990 VL HIV MON-24 2 A 6 3

AM Patient 3 MHOM/FR/2002/LPN202 2002 IVL MON-1 3 A 4 1

P MCAN/FR/2000/LPM206 2000 CanL MON-1 4 A 4 1

AM Patient 4 MHOM/FR/2003/LPN212 2003 VL HIV MON-1 4 A 4 1

AM Patient 4 MHOM/FR/2004/LPN243 2004 RVL HIV MON-1 4 A 4 1

AM Patient 5 MHOM/FR/90/LPN67 1990 VL HIV MON-1 5 A 4 1

AM Patient 6 MHOM/FR/96/LPN126 1996 IVL MON-1 6 A 4/3 1

P Patient 7 MHOM/FR/93/LPM110 1993 VL HIV MON-11 7 A 4/6 1/3

AM Patient 8 MHOM/FR/90/LPN62 1990 VL MON-1 8 B 1

AM Patient 9 MHOM/FR/98/LPN163 1998 IVL MON-1 9 B 1

P Patient 10 MHOM/FR/96/LPM150 1996 VL HIV MON-1 10 A 4/5 1/2

AM Patient 11 MHOM/FR/2001/LPN192 2001 IVL MON-1 11 B/

A

CE MCAN/FR/2006/LPN278 2006 CanL MON-1 12 A 4/5 1/2

P Patient 12 MHOM/FR/97/LPM180 1997 VL HIV MON-1 13 A 5 2

P MCAN/FR/2000/LPM207 2000 CanL MON-1 13 A 5 2

P Patient 13 MHOM/FR/2009/LPM262 2009 VL HIV MON-1 13 A 5 2

P Patient 14 MHOM/FR/2000/LPM197 2000 VL HIV MON-1 14 A 5 2

AM Patient 15 MHOM/FR/97/LPN161 1997 CL MON-1 15 A 1 4

CO Patient 16 MHOM/FR/97/LPN154 1997 VL MON-1 16 A 6 3

P Patient 17 MHOM/FR/2002/LPM225 2002 VL HIV MON-1 17 A 5 2

P Patient 18 MHOM/FR/2002/LPM215 2002 VL HIV MON-1 17 A 5 2

P Patient 19 MHOM/FR/2000/LPM

195

2000 VL HIV MON-1 18 A 2/5/3 1/3/2

AM Patient 20 MHOM/FR/86/LPN30 1986 VL HIV MON-1 19 A/

B

AM Patient 21 MHOM/FR/88/LPN50 1988 VL HIV MON-1 20 A 5 2

AM Patient 29 MHOM/FR/84/LPN23 1984 VL MON-1 21 A 5 2

AM Patient 30 MHOM/FR/85/LPN25a 1985 VL MON-1 21 A 5 2

AM Patient 31 MHOM/FR/94/LPN112 1994 VL MON-1 21 A 5 2

P Patient 22 MHOM/FR/96/LPM151 1996 VL HIV MON-1 21 A 5 2

AM Patient 32 MHOM/FR/96/LPN132 1996 VL MON-1 21 A 5 2

P Patient 23 MHOM/FR/97/LPM169 1997 VL HIV MON-1 21 A 5 2

P Patient 24 MHOM/FR/97/LPM172 1997 VL HIV MON-1 21 A 5 2

P Patient 35 MHOM/FR/2004/LPN228 2004 IVL MON-1 21 A 5 2

P Patient 25 MHOM/FR/2005/LPM242 2005 IVL MON-1 21 A 5 2

P Patient 26 MHOM/FR/2005/LPM247 2005 IVL MON-1 21 A 5 2

P Patient 27 MHOM/FR/2009/LPM261 2009 IVL MON-1 21 A 5 2

AM MCAN/FR/95/LPN122* CanL MON-1 21 A 5 2

AM MCAN/FR/95/LPN123* CanL MON-1 21 A 5 2

AM MCAN/FR/95/LPN124* CanL MON-1 21 A 5 2

AM Patient 33 MHOM/FR/96/LPN136* 1996 AC MON-1 21 A 5 2

AM Patient 34 MHOM/FR/96/LPN131* 1996 AC MON-1 21 A 5 2

AM Patient 28 MHOM/FR/81/LPN5 1981 IVL MON-1 21 A 5 2

AM Patient 36 n. d. 2009 IVL MON-1 21 A 5 2

(Continued)

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K = 6 K = 4 K = 2

AM Patient 37 MHOM/FR/90/LPN61 1990 IVL MON-1 22 A/

B

AM Patient 38 MHOM/FR/2002/LPN199 2002 VL MON-1 23 A 3 1

P Patient 39 MHOM/FR/2007/LPM255 2007 IVL MON-1 24 A 4/5/2 1

P Patient 40 MHOM/FR/2002/LPM216 2002 VL HIV MON-1 25 A 4/3/2 1

P Patient 41 MHOM/FR/2002/LPM217 2002 VL MON-1 25 A 4/3/2 1

P Patient 42 MHOM/FR/98/LPM185 1998 VL HIV MON-1 26 A 4/5/6 1

CO Patient 43 MHOM/FR/2006/LPM251 2006 IVL MON-24 27 A 2 1

AM Patient 44 MHOM/FR/2001/LPN195 2001 VL MON-1 28 A 5/2/4 1/2

AM Patient 45 MHOM/FR/2007/LPN312 2007 IVL MON-1 29 A 3 1

AM MCAN/FR/86/LPN28 1986 CanL MON-1 30 A 3 1

P Patient 46 MHOM/FR/2003/LPN221 2003 CL MON-1 31 A 3/2 1

AM Patient 47 MHOM/FR/97/LPN159 1997 VL MON-1 32 B/

A

AM Patient 48 MHOM/FR/90/LPN64 1990 VL HIV MON-1 33 A 3 1

AM Patient 49 MHOM/FR/89/LPN54 1989 VL MON-1 34 B 1

AM Patient 50 MHOM/FR/91/LPN70 1991 IVL MON-1 34 B 1

AM Patient 51 MHOM/FR/92/LPN78 1992 VL MON-1 34 B 1

AM Patient 52 MHOM/FR/95/LPN116 1995 VL HIV MON-1 34 B 1

AM Patient 53 MHOM/FR/96/LPN141 1996 VL MON-1 34 B 1

AM Patient 54 MHOM/FR/97/LPN150 1997 IVL MON-1 34 B 1

AM Patient 55 MHOM/FR/2001/LPN181 2001 IVL MON-1 34 B 1

AM Patient 56 MHOM/FR/2007/LPN313 2007 CL MON-1 34 B 1

AM Patient 57 MHOM/FR/2011/LPN358 2011 VL MON-1 34 B 1

AM MCAN/FR/89/LPN57 1989 CanL MON-1 35 A/

B

AM Patient 58 MHOM/FR/95/LPN120 1995 VL HIV MON-1 35 A/

B

AM Patient 60 MHOM/FR/92/LPN84 1992 IVL MON-1 36 A 3 1

AM Patient 61 MHOM/FR/94/LPN103 1994 CL MON-1 36 A 3 1

AM Patient 62 MHOM/FR/95/LPN115 1995 IVL MON-1 36 A 3 1

AM Patient 63 MHOM/FR/95/LPN119 1995 VL HIV MON-1 36 A 3 1

CO Patient 59 MHOM/FR/96/LPM157 1996 VL MON-1 36 A 3 1

AM Patient 64 MHOM/FR/2001/LPN187 2001 VL MON-1 36 A 3 1

AM Patient 64 MHOM/FR/2002/LPN198 2002 RVL MON-1 36 A 3 1

P Patient 65 MHOM/FR/94/LPM112 1994 VL HIV MON-1 37 A 4/5/1 1/2/4

P Patient 66 MHOM/FR/2006/LPM250 2006 VL MON-1 37 A 4/5/1 1/2/4

AM Patient 67 MHOM/FR/93/LPN92 1993 VL HIV MON-1 38 A 2/1/3 3/4/1

P Patient 68 MHOM/FR/97/LPM173 1997 VL MON-1 39 B 1

AM Patient 69 MHOM/FR/86/LPN29 1986 VL HIV MON-1 40 A/

B

AM Patient 71 MHOM/FR/87/LPN33 1987 IVL MON-1 41 A/

B

AM MCAN/FR/87/LPN34 1987 CanL MON-1 41 A/

B

AM Patient 72 MHOM/FR/89/LPN51 1989 VL HIV MON-1 41 A/

B

(Continued)

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K = 6 K = 4 K = 2

AM Patient 73 MHOM/FR/98/LPN164 1998 VL HIV 41 A/

B

AM Patient 70 MHOM/FR/2005/LPM244 2005 VL HIV MON-1 41 A/

B

AM Patient 74 MHOM/FR/96/LPN146 1996 VL HIV MON-1 42 B 2

AM Patient 75 MHOM/TR/94/LPN101 1994 IVL MON-1 43 B 1

AM Patient 76 MHOM/FR/94/LPN104 1994 IVL MON-1 43 B 1

AM Patient 77 MHOM/FR/95/LPN113 1995 IVL MON-1 43 B 1

AM Patient 78 MHOM/FR/95/LPN121 1995 VL HIV MON-1 43 B 1

AM Patient 86 MHOM/FR/2002/LPN201 2002 RVL HIV MON-1 43 B 1

AM Patient 87 MHOM/FR/2004/LPN233 2004 VL HIV MON-1 43 B 1

AM Patient 79 MHOM/FR/96/LPN134* 1996 AC MON-1 43 B 1

AM Patient 80 MHOM/FR/96/LPN137* 1996 AC MON-1 43 B 1

AM Patient 81 MHOM/FR/96/LPN138* 1996 AC MON-1 43 B 1

AM Patient 82 MHOM/FR/96/LPN144* 1996 AC MON-1 43 B 1

AM Patient 83 MHOM/FR/96/LPN143* 1996 AC MON-1 43 B 1

AM Patient 84 MHOM/FR/96/LPN142* 1996 AC MON-1 43 B 1

AM Patient 85 MHOM/IT/96/LPN145* 1996 AC MON-1 43 B 1

AM Patient 88 MHOM/FR/80/LPN3 1980 IVL MON-1 44 B 1

AM Patient 89 MHOM/00/94/LPN108 1994 VL HIV MON-1 44 B 1

AM Patient 90 MHOM/FR/2004/LPN236 2004 VL MON-1 45 B 1

AM MCAN/FR/82/LPN16 1983 CanL MON-1 46 B 1

AM Patient 91 MHOM/FR/83/LPN19 1983 VL MON-1 46 B 1

AM Patient 92 MHOM/FR/84/LPN20 1984 VL MON-1 46 B 1

AM Patient 93 MHOM/FR/85/LPN24 1985 VL MON-1 46 B 1

AM MCAN/FR/87/LPN37 1987 CanL MON-1 46 B 1

AM Patient 94 MHOM/FR/88/LPN46 1988 VL MON-1 46 B 1

AM Patient 95 MHOM/FR/89/LPN59 1989 VL HIV MON-1 46 B 1

AM Patient 96 MHOM/FR/93/LPN91 1993 IVL MON-1 46 B 1

AM Patient 97 MHOM/00/93/LPN94 1993 VL HIV MON-1 46 B 1

AM Patient 98 MHOM/FR/95/LPN107 1994 IVL MON-1 46 B 1

AM Patient 99 MHOM/FR/95/LPN114 1994 IVL MON-1 46 B 1

AM Patient

100

MHOM/FR/95/LPN118 1995 VL HIV MON-1 46 B 1

AM Patient

101

MHOM/FR/96/LPN125 1996 VL MON-1 46 B 1

AM Patient

102

MHOM/FR/97/LPN148 1997 VL HIV MON-1 46 B 1

P Patient

105

MHOM/FR/97/LPM139 1995 VL HIV MON-1 46 B 1

AM Patient

103

MHOM/FR/97/LPN152 1997 VL MON-1 46 B 1

AM Patient

104

MHOM/FR/2001/LPN180 2001 IVL MON-1 46 B 1

AM Patient

106

MHOM/FR/2005/LPN257 2005 IVL MON-1 47 B 1

AM Patient

107

MHOM/FR/84/LPN21 1984 VL MON-1 48 B 1

(Continued)

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K = 6 K = 4 K = 2

AM Patient

108

MHOM/FR/92/LPN85 1992 IVL MON-1 48 B 1

AM Patient

109

MHOM/FR/2004/LPN240 2004 VL MON-1 48 B 1

AM Patient

110

n. d. 2011 IVL MON-1 49 B 1

AM Patient

111

MHOM/FR/92/LPN86 1992 IVL MON-1 50 B 2

AM Patient

112

MHOM/FR/2001/LPN191 2001 VL HIV MON-1 50 B 2

AM Patient

113

MHOM/FR/2008/LPN321 2008 VL MON-1 50 B 2

AM Patient

114

MHOM/FR/99/LPN170 1999 VL MON-1 51 B 2

AM Patient

115

MHOM/FR/2006/LPN281 2006 VL MON-1 52 B 2

CE MCAN/FR/2006/LPN285 2006 CanL MON-1 52 B 2

AM Patient

116

MHOM/FR/87/LPN36 1987 VL HIV MON-1 53 B 2

AM Patient

117

MHOM/FR/91/LPN71 1991 VL HIV MON-1 53 B 2

AM Patient

118

MHOM/FR/93/LPN96 1992 VL MON-1 53 B 2

AM Patient

119

MHOM/FR/93/LPN99 1993 VL HIV MON-1 53 B 2

AM MCAN/FR/94/LPN102 1994 CanL MON-1 53 B 2

AM Patient

120

MHOM/FR/95/LPN117 1995 VL MON-1 53 B 2

AM Patient

121

MHOM/FR/2001/LPN189 2001 VL MON-1 53 B 2

AM Patient

122

MHOM/FR/78/LPN1 1978 VL MON-1 54 B 2

AM MCAN/FR/82/LPN6 1982 CanL MON-1 55 B 2

AM Patient

123

MHOM/FR/84/LPN22 1983 VL MON-1 55 B 2

AM Patient

124

MHOM/FR/86/LPN31 1986 VL MON-1 55 B 2

AM Patient

125

MHOM/FR/88/LPN48 1988 CL MON-1 55 B 2

AM Patient

126

MHOM/FR/89/LPN55 1989 IVL MON-1 55 B 2

AM Patient

127

MHOM/FR/90/LPN68 1990 IVL MON-1 55 B 2

AM Patient

128

MHOM/FR/92/LPN76 1992 VL MON-1 55 B 2

AM Patient

129

MHOM/FR/92/LPN77 1992 VL HIV MON-1 55 B 2

AM Patient

130

MHOM/FR/92/LPN80 1992 VL HIV MON-1 55 B 2

AM Patient

131

MHOM/FR/92/LPN82 1992 VL HIV MON-1 55 B 2

(Continued)

(9)

K = 6 K = 4 K = 2

CO Patient

146

MHOM/FR/93/LPN95 1993 VL MON-1 55 B 2

AM Patient

132

MHOM/FR/94/LPN106 1994 VL MON-1 55 B 2

AM Patient

133

MHOM/FR/94/LPN109 1994 VL HIV MON-1 55 B 2

AM Patient

135

MHOM/FR/96/LPN133 1996 IVL MON-1 55 B 2

AM Patient

134

MHOM/FR/96/LPN130 1996 VL MON-1 55 B 2

AM MFEL/FR/96/LPN139 1996 CatL MON-1 55 B 2

AM Patient

136

MHOM/FR/97/LPN155 1997 VL MON-1 55 B 2

AM Patient

137

MHOM/FR/97/LPN158 1997 VL MON-1 55 B 2

AM Patient

139

MHOM/FR/2000/LPN176 2000 VL MON-1 55 B 2

AM Patient

138

MHOM/FR/2000/LPN175 2000 VL MON-1 55 B 2

AM Patient

140

MHOM/FR/2003/LPN209 2003 IVL MON-1 55 B 2

AM Patient

141

MHOM/FR/2003/LPN217 2003 VL MON-1 55 B 2

AM Patient

142

MHOM/FR/2006/LPN259 2006 VL MON-1 55 B 2

AM Patient

143

MHOM/FR/2006/LPN282 2006 IVL MON-1 55 B 2

AM Patient

144

MHOM/FR/2007/LPN316 2007 VL MON-1 55 B 2

AM Patient

145

MHOM/FR/2011/LPN357 2011 VL MON-1 55 B 2

AM Patient

147

MHOM/FR/96/LPN127 1996 VL HIV MON-1 56 B 2

AM MCAN/FR/82/LPN10 1982 CanL MON-1 57 B 2

AM Patient

148

MHOM/FR/89/LPN53 1989 VL MON-1 57 B 2

AM Patient

149

MHOM/FR/90/LPN66 1990 VL MON-1 57 B 2

AM Patient

150

MHOM/FR/93/LPN90 1993 VL MON-1 57 B 2

AM Patient

151

MHOM/FR/93/LPN93 1993 IVL MON-1 57 B 2

AM Patient

152

MHOM/FR/93/LPN98 1993 VL HIV MON-1 57 B 2

AM Patient

153

MHOM/FR/94/LPN110 1994 VL HIV MON-1 57 B 2

AM Patient

154

MHOM/FR/96/LPN140 1996 IVL MON-1 57 B 2

AM Patient

155

MHOM/FR/97/LPN156 1997 VL HIV MON-1 57 B 2

AM Patient

156

MHOM/FR/2000/LPN178 2000 IVL MON-1 57 B 2

(Continued)

(10)

K = 6 K = 4 K = 2

AM Patient

157

MHOM/FR/2001/LPN190 2001 IVL MON-1 57 B 2

AM Patient

158

MHOM/FR/2006/LPN277 2006 VL MON-1 57 B 2

AM Patient

159

MHOM/FR/2011/LPN351 2011 IVL MON-1 57 B 2

AM Patient

160

MHOM/FR/2011/LPN356 2011 IVL MON-1 57 B 2

AM Patient

161

MHOM/FR/2011/LPN366 2011 IVL MON-1 57 B 2

AM Patient

162

MHOM/FR/2004/LPN237 2004 VL MON-1 58 B 2

CO Patient

163

MHOM/FR/94/LPN105 1994 VL HIV MON-1 59 B 1

P Patient

164

MHOM/FR/96/LPM154 1996 IVL MON-1 60 A 3/4/5/2 1

P Patient

165

MHOM/FR/97/LPM174 1997 VL HIV MON-1 61 A 4/3/2 1

AM Patient

166

MHOM/FR/99/LPN173 1999 IVL MON-1 62 A/

B

P Patient

167

MHOM/FR/97/LPM170 1997 IVL MON-1 63 A 1 4

P Patient

168

MHOM/FR/97/LPM177 1997 VL HIV MON-1 63 A 1 4

P Patient

169

MHOM/FR/2000/LPM201 2000 VL HIV MON-1 63 A 1 4

P Patient

170

MHOM/FR/2001/LPM209 2001 VL HIV MON-1 64 A 1/3/4/2 4/1/2

P Patient

171

MHOM/FR/97/LPM166 1997 VL HIV MON-1 65 A 1 4

P Patient

172

MHOM/FR/2004/LPM236 2004 IVL MON-1 66 A 1 4

P Patient

173

MHOM/FR/2006/LPM252 2006 VL MON-1 67 A 1 4

P Patient

174

MHOM/FR/94/LPM116 1994 VL HIV MON-1 68 A 1 4

P Patient

175

MHOM/FR/96/LPM138 1996 VL HIV MON-1 68 A 1 4

P Patient

176

MHOM/FR/99/LPM189 1999 IVL MON-1 68 A 1 4

P Patient

177

MHOM/FR/2000/LPM204 2000 IVL MON-1 68 A 1 4

P Patient

178

MHOM/FR/98/LPM183 1998 VL HIV MON-1 69 A 1/3/2 4

P Patient

179

MHOM/FR/97/LPM178 1997 UK MON-1 69 A 1/3/2 4

P Patient

180

MHOM/FR/2003/LPM232 2003 IVL MON-1 70 A 1 4

P Patient

181

MHOM/FR/96/LPM152 1996 VL MON-1 71 A 1/3/2 4

P Patient

182

MHOM/FR/97/LPM168 1997 VL HIV MON-1 72 A 1 4

(Continued)

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K = 6 K = 4 K = 2

P Patient

183

MHOM/FR/98/LPM181 1998 MCL MON-1 73 A 5 2

P Patient

184

MHOM/FR/96/LPM156 1996 IVL MON-1 74 A 5/1/4/2 2/4/1

CE IPER/FR/84/LEM576* 1984 PHLE MON-1 75 A 4/1/2 1/4

CE IARI/FR/84/LEM595* 1984 PHLE MON-1 75 A 4/1/2 1/4

AM Patient

185

MHOM/FR/96/LPN129 1996 VL HIV MON-1 76 A 1 4

AM Patient

186

MHOM/FR/88/LPN45 1988 VL HIV MON-1 77 A 1 4

AM Patient

187

MHOM/FR/89/LPN58 1989 IVL MON-1 77 A 1 4

AM Patient

188

MHOM/FR/91/LPN69 1991 VL HIV MON-1 77 A 1 4

AM Patient

189

MHOM/FR/96/LPN128 1996 VL HIV MON-1 77 A 1 4

AM Patient

190

MHOM/FR/97/LPN151 1996 VL HIV MON-1 77 A 1 4

AM Patient 86 MHOM/FR/97/LPN153 1997 VL HIV MON-1 77 A 1 4

AM MCAN/FR/98/LPN168 1998 CanL 77 A 1 4

AM Patient 86 MHOM/FR/2000/LPN177 2000 RVL HIV MON-1 77 A 1 4

AM Patient 86 MHOM/FR/2001/LPN185 2001 RVL HIV MON-1 77 A 1 4

AM Patient

191

MHOM/FR/2001/LPN186 2001 VL HIV MON-1 77 A 1 4

AM Patient 86 MHOM/FR/2003/LPN215 2003 RVL HIV MON-1 77 A 1 4

AM Patient

192

MHOM/FR/2007/

LPN314* 2007 VL HIV MON-1 78 A 1/6 4/3/1

AM MCAN/FR/2006/LPN267 2006 CanL MON-1 79 A 1/6/3/4 4/2/3

P Patient

193

MHOM/FR/2002/LPM222 2002 VL HIV MON-1 80 A 1/5/6 4/2

P Patient

194

MHOM/FR/2001/LPM214 2001 VL MON-1 81 A 2/4 1

P Patient

195

MHOM/FR/2002/LPM226 2002 VL HIV MON-1 82 A 2/4 1

P Patient

196

MHOM/FR/2002/LPM228 2002 VL MON-1 83 A 2/4 1

P Patient

197

MHOM/FR/96/LPM155 1996 VL MON-1 84 A 2/3/1 1

P Patient

198

MHOM/FR/96/LPM159 1996 VL MON-1 84 A 2/3/1 1

P Patient

199

MHOM/FR/94/LPM133 1994 VL HIV MON-1 85 A 2 1

P Patient

200

MHOM/FR/96/LPM161 1996 IVL HIV MON-1 85 A 2 1

P Patient

201

MHOM/FR/2009/LPM264 2009 MCL MON-1 85 A 2 1

P Patient

202

MHOM/FR/94/LPM122-2 1994 VL HIV MON-1 86 A 1/3/4 4/1

P Patient

203

MHOM/FR/2001/LPM212 2001 CL MON-1 87 A 4/3/2 1

(Continued)

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K = 6 K = 4 K = 2

P Patient

204

MHOM/FR/2008/LPM260 2008 VL HIV MON-1 88 A 2 1/3

P Patient

205

MHOM/FR/99/LPM191 1999 CL HIV MON-1 89 A 1/3 1/4

P Patient

206

MHOM/FR/95/LPM137 1995 VL HIV MON-1 90 A 3/6 1/3

P Patient

207

MHOM/FR/2000/LPM196 2000 VL HIV MON-1 91 A 4 1

P Patient

208

MHOM/FR/94/LPM118 1994 VL HIV MON-

108

92 A 4/1/5 1/2/4

CE Patient

212

MHOM/FR/85/LEM716* 1985 VL MON-1 93 A 4 1

P Patient

210

MHOM/FR/97/LPM176 1997 IVL MON-1 93 A 4 1

CO Patient

209

MHOM/FR/98/LPM186 1998 VL MON-1 93 A 4 1

P Patient

211

MHOM/FR/2001/LPN183 2001 VL MON-1 93 A 4 1

AM Patient

213

MHOM/FR/83/LPN18 1983 VL MON-1 94 A 4 1

CE Patient

214

MHOM/FR/87/LEM1098* 1987 CL MON-1 94 A 4 1

CE Patient

215

MHOM/FR/78/LEM75* 1978 VL MON-1 94 A 4 1

CE Patient

216

MHOM/FR/85/LEM663* 1985 VL MON-1 95 A 4 1

AM Patient

217

MHOM/FR/88/LPN41 1988 VL HIV MON-1 96 A 2/5 3/2

AM Patient

218

MHOM/FR/2003/LPN213 2003 VL MON-1 97 A 4 1

AM Patient

219

MHOM/FR/96/LPM162 1996 CL MON-24 98 A 6 3

AM Patient

220

MHOM/00/2004/LPN234 2004 CL MON-24 99 A 6 3

AM Patient

190

MHOM/FR/2001/LPN182 2001 RVL HIV MON-1 100 A 1 4

AM Patient

190

MHOM/FR/2001/LPN188 2001 RVL HIV MON-1 100 A 1 4

P Patient

221

MHOM/FR/2000/LPM200 2000 VL HIV MON-1 101 A 2/1 1/3/4

P Patient

222

MHOM/FR/94/LPM120 1994 VL HIV MON-1 102 A 2/1/3 1/4

P Patient

223

MHOM/FR/99/LPM194 1999 MCL MON-1 103 A 4/3/2 1

P Patient

224

MHOM/FR/96/LPM158 1996 VL MON-1 104 A 4/2/5 1/2

AM MCAN/FR/80/LPN4 1980 CanL MON-1 105 A 4/3/2 1

AM MCAN/FR/82/LPN8 1982 CanL MON-1 105 A 4/3/2 1

AM Patient

225

MHOM/FR/99/LPN171 1999 IVL MON-1 106 A 3 1

P Patient

226

MHOM/FR/2001/LPM211 2001 VL HIV MON-1 107 A 3 1

(Continued)

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strain MHOM/FR/85/LEM716 was used as a control to determine the size of amplified micro- satellite fragments, as this microsatellite data have been published [9].

Multi-Locus Microsatellite Typing (MLMT)

Twelve microsatellite loci were amplified using the PCR conditions as previously described:

LiBTG, LiBTA, LIST7021, LIST7025, LIST7026, LIST7031, LIST7033, Li22-25, Li45-24, TubCA, Li71-5/2 and Rossi2 [9 – 12]. The amplification products were analyzed using an auto- mated capillary ABI Prism 3130XL Genetic Analyzer (Applied Biosystems, France). The data were stored and analyzed using GeneMapper analysis software (version 4.0, Applied Biosys- tems). PCR fragment sizes were determined using the internal size standard GeneScan 500 LIZ (Applied Biosystems). All 270 Leishmania isolates were genotyped at each of the 12 loci. With the PCR fragment size of the control strain MHOM/FR/85/LEM716, we were able to include

K = 6 K = 4 K = 2

P Patient

227

MHOM/00/00/LPM148 1995 UK MON-1 108 A 3 1

AM Patient

228

n. d. 2011 VL MON-1 109 A 3 1

AM MCAN/FR/86/LPN27 1986 CanL MON-1 110 A 3 1

AM Patient

229

MHOM/FR/99/LPN174 1999 CL MON-24 111 A 6 3

AM Patient

230

MHOM/FR/2005/LPN253 2001 VL HIV MON-80 112 A 6 3

P Patient

231

MHOM/00/2003/LPM233 2003 IVL MON-1 113 A 2 3

CO Patient

232

MHOM/FR/2000/LPM205 2000 VL MON-1 114 A 6 3

CO Patient

233

MHOM/FR/92/LPN83 1991 CL HIV MON-1 115 A 6 3

CO Patient

234

MHOM/FR/99/LPM190 1999 VL HIV MON-1 116 A 6 3

AM Patient

235

MHOM/FR/89/LPN60 1989 VL HIV MON-1 117 A 2 1/3

P Patient

236

MHOM/FR/2008/LPM259 2008 VL HIV MON-1 118 A 2/1 1/4/3

P Patient

237

MHOM/FR/2007/LPM254 2007 IVL MON-1 119 A 6 3

AM Patient

238

MHOM/FR/93/LPN97 1993 CL MON-24 120 A 6 3

P Patient

239

MHOM/FR/95/LPM136 1995 VL HIV MON-1 121 A 6 3

Legend of columns: Endemic area: AM: Alpes-Maritimes; P: Provence; CE: Cévennes; CO: Corsica. Patients: Anonymized name given to the patients.

Sample WHO code: WHO code of the isolates; The MLMT profile of the samples indicated with*was already characterized by Hide et al [9]; n. d. = not defined. Y: Year of isolation. C F / H: Clinical form of the disease and/or host: VL–visceral leishmaniasis; IVL–Infant under 15 years with visceral leishmaniasis; CL–cutaneous leishmaniasis; MCL–muco-cutaneous leishmaniasis; RVL—New episode of leishmaniasis in VL patient; AC–asymptomatic carrier; CanL–canine leishmaniasis; CatL–leishmaniasis in cat; PHLE–sample isolated from phlebotomine sandfly; UK–unknown. Zymo: zymodeme of isolate. G: genotypes. P: population as defined by STRUCTURE.

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microsatellite data from the Hide et al. study (data indicated with an asterisk in Table 1). Four isolates from this previous study (MCAN/FR/95/LPN122, MCAN/FR/95/LPN123, MCAN/FR/

95/LPN124, and MCAN/FR/95/LPN124) were re-extracted from culture and re-genotyped blindly. The same microsatellite results described by Hide et al. were obtained [8].

Genetic diversity and differentiation analysis

Descriptive statistics for the observed genetic populations were calculated using Genetix ver- sion 4.05.2 (2004) and FSTAT Version 2.9.3.2 [13]. Using these programs, we calculated allelic diversity (number of allelic variants per maker), expected ( He ) and observed ( Ho ) heterozygos- ity, genetic diversity within subsamples Hs, inbreeding coefficient (F

IS

) the migration rates (gene flow) ( Nm ) [14]. The Fst value, which indicates the degree of genetic differentiation and gene flow among populations was also calculated. Fst values above 0.25 with significant p- values ( < 0.05) indicated strong genetic differentiation [15].

Clustering and phenetic analyses

Phylogenetic analyses were performed based on the microsatellite profiles. A distance matrix was calculated using the Chord distance (Cavalli-Sforza and Edwards 1967) setting in the POP- ULATIONS 1.2.31 software with bootstrap values determined for 1,000 replicates (http://

bioinformatics.org/~tryphon/populations/) [16]. The resulting distance matrix was processed using MEGA 4.0.2 to construct an unrooted Neighbor-Joining (NJ) tree [17].

Fig 1. Geographical distribution of isolates from Southeastern France.Isolates clustered into four endemic areas. The geographic areas where samples were isolated from Cévennes (blue), Provence (green), Alpes-Maritimes (red) and Corsica (violet) are indicated. The Alpes-Maritimes and Provence endemic areas are located in the PACA region.

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tions. A series of ten independent runs was performed for each K value between one and ten.

The following parameters were used: burn in period of 20,000 iterations, 200,000 Markov Chain Monte Carlo iterations and admixture model. The most probable number of clusters was identified via calculation of the Delta K (ΔK), which is based on the rate of change in the log probability of data between successive K values. The peak of the ΔK graph corresponds to the most probable number of populations in the data set [19].

Statistical analysis

A chi-square statistical test was performed to determine whether the observed data differed sig- nificantly from the expected ratios. The chi-square value was considered significant when p 0.05. This test was used to compare the proportion of HIV+ patients in Populations A and B.

Results

Microsatellite analysis

In total, 270 isolates were typed at 12 microsatellite markers with one or two alleles at each locus. All markers were polymorphic. The number of alleles per locus ( N a) ranged from 3 to 13. Li22-35, LIST7021, LiBTG, LiBTA and LIST7026 were the most polymorphic markers with 13, 12, 10, 9 and 8 alleles, respectively. LIST7031, Li71-5/2 and LIST7025 were the least poly- morphic markers with three different alleles (Table 2).

Genetic variability was analyzed among the 12 microsatellite loci (Table 2). The Ho was weak and ranged from 0.011 to 0.174 for Li71-5/2 and LiBTA, respectively, with an overall Ho at 0.044.

The mean intra-population Hs was 0.546 (0.224 – 0.811) for the entire sample set and 0.531 (0.208–0.804) for the MON-1 population (Table 2). The F

IS

for the entire population was 0.920, thereby indicating a considerable degree of inbreeding. A separate analysis was performed to investigate the genetic polymorphisms among the four geographically determined populations (Table 3). Extensive inbreeding in the four populations was observed, with the highest inbreeding coefficient found in the populations of the CO and AM endemic areas. The genetic differentia- tion among the four endemic areas was tested using FSTAT version 2.9.3.2 (Table 4). The F st val- ues ranged from 0.067 to 0.321. All Fst values between the four endemic areas were significant.

We obtained lower values for P versus CE and P versus CO and higher values for AM versus CE and CO versus CE (which may be due to the low number of isolates collected from CE and CO).

When comparing AM and P samples from 1993 to 2009 (corresponding to the time period of the isolation of samples from the P endemic area used in this study), the Fst value obtained was simi- lar to the F st value corresponding to the complete period of sample collection (1978 to 2011).

Sub-populations were also defined according to their position in relation to Vars River (S1

Table). This river is located in the southeast of France and flows in the Alpes-Maritimes

Department. The Fst values highlighted a gradient of differentiation from the East Vars to the

West Vars and up to the P endemic area. A high and significant genetic differentiation

(Fst = 0.308) was obtained when comparing isolates from east of the Vars River and the P

endemic area. The comparison of sub-populations isolated from the P endemic area failed to

show any genetic differentiation (Marseille versus Toulon or Marseille versus other cities in the

P endemic area), with the limitation that few samples were collected from Toulon (n = 7).

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Geographical distribution of isolates from the two main endemic areas of AM and P

A total of 121 different genotypes were identified from the 270 isolates corresponding to a geno- type frequency of 0.037. The entire sample set comprised 91 unique genotypes (75%). Among the 30 repeated genotypes, seven were common to two endemic areas, one was common to three endemic areas and 22 pertained to the same focus (Fig 2). The genotypes 21 (primarily) and 46 were found in both endemic areas of AM and P (Fig 2). Within these endemic areas, Faucher et al. have described high- and low-risk sub-areas of VL [5]. In our study, the repeated genotypes were almost exclusively found in high-risk areas, with the only exception of genotype 21 which was found in high and low risk sub-areas (Fig 3A and 3B). Among the 30 repeated genotypes, 11 were found in four or more samples. These 11 genotypes represented 132 isolates.

Temporal analysis of genotypes

The isolates were collected over the course of a 33-year period from 1978 to 2011 (Fig 4). The repeated genotypes, found in four or more samples, were isolated over a period of six (genotype 68) to 29 years (genotypes 57 and 55). All genotypes except 68, 36, 34 and 43 were isolated from both humans and dogs. Genotype 21 was found to be present in the AM and P endemic areas over the course of 28 years. This genotype was first isolated in 1981 in the AM endemic

LiBTG 10 0.620 0.041 0.621 0.935

LiBTA 9 0.809 0.174 0.811 0.786

LIST7026 8 0.690 0.033 0.691 0.952

TubCA 7 0.541 0.041 0.542 0.925

Li45-24 6 0.649 0.026 0.650 0.960

Rossi2 6 0.553 0.019 0.554 0.967

LIST7033 6 0.533 0.019 0.534 0.965

LIST7031 3 0.230 0.026 0.231 0.888

LIST7025 3 0.240 0.019 0.224 0.918

Li71-5/2 3 0.502 0.011 0.503 0.978

Overall 7.17 0.545 0.044 0.546 0.920

Na: number of alleles per locus;He: expected heterozygosity;Ho: observed heterozygosity;Hs: genetic diversity;FIS: inbreeding coefficient.

doi:10.1371/journal.pntd.0004303.t002

Table 3. Genetic diversity among the four endemic areas based on the MLMT profiles of the 12 ana- lyzed markers.

Na He Ho FIS

AM 6.333 0.462 0.030 0.936

P 5.417 0.498 0.079 0.844

CO 3.000 0.568 0.028 0.956

CE 2.250 0.281 0.042 0.869

Na: Number of alleles per locus,He: expected heterozygosity,Ho: observed heterozygosity,FIS: inbreeding coefficient.

AM = Alpes-Maritimes, P = Provence, CO = Corsica and CE = Cévennes.

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area and then in 1996, at which time it was first identified in both the AM and P endemic areas. After 1996, genotype 21 was only isolated in the P. Finally, in 2009, this genotype was found in both the AM and P endemic areas. Genotype 21 was isolated from a variety of patients including asymptomatic carriers (AC), adult VL, infant VL and HIV+ VL cases.

Relapse and re-infection

Four patients (patients 4, 64, 86 and 190) experienced more than one episode of VL (Table 1).

Three of these patients were HIV+ (patients 4, 86 and 190). The isolates derived from patient 4 and 64 (HIV+ and HIV-, respectively), which were collected during a first VL episode (2003 for patient 4 and 2001 for patient 64) and second VL episode (one year later), presented identical MLMT profiles. In both cases, relapse was suspected. Patient 190 (HIV+) presented three episodes of VL, for which the second and third (2001 for both episodes) isolates differed from the first

P vs. AM 75 / 178 0.239 0.008

P vs. CO 75 / 9 0.126 0.008

P vs. CE 75 / 8 0.067 0.050

CO vs. CE 9 / 8 0.270 0.008

AM vs. CO 178 / 9 0.161 0.008

AM vs. CE 178 / 8 0.321 0.008

P vs. AM isolates collected during same period of time (1993 to 2009)

75 / 111 0.236 0.050

Sub-population defined according to their position in relation to the Vars river

AM East Vars vs. AM West Vars 122 / 50 0.062 0.050

AM West Vars vs. P 52 / 75 0.144 0.050

P vs. AM East Vars 75 / 122 0.308 0.050

Sub-population within the P endemic area

Within P: Marseille vs. Toulon 42 / 7 0.033 0.850

Within P: Marseille vs. Other cities In P 42 / 33 0.012 0.550 doi:10.1371/journal.pntd.0004303.t004

Fig 2. Repeated genotypes.Arbitrary numbers assigned to the 30 repeated genotypes in (x-axis) and number of isolates belonging to each genotype (y- axis). The origin of each isolates is indicated by the different colors.

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Fig 3. A. Localization of the genotypes.Eleven repeated genotypes, which were observed in four or more isolates, are represented with colored squares on the map of the endemic areas of Alpes-Maritimes and Provence. The two endemic areas are separated by a blue line. The remaining genotypes are represented by light brown squares. The area in the black rectangle is shown in further detail in Fig 3B. B. Detailed localization of isolates in the Alpes- Maritimes endemic area and more precisely the surrounding region of Nice. Isolates were localized at the city level. The black line represents the delimitation of Nice.

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isolate (1996) at only one marker (LIST7021). Re-infection was suspected for this patient; however, further studies are warranted to confirm whether only one allelic change can lead to the suspicion of a re-infection or reflects the evolution of the isolate over time. Patient 86 (HIV+) presented five different episodes of VL due to active chronic VL [20]. Isolates from the second (2000), third (2001) and last episode (2003) presented with the same MLMT profile compared with the isolate from the initial infection (1997). However, the MLMT profile of the fourth episode (2002) isolate varied at 11 loci; only Rossi2 remained the same. Re-infection and relapse were suspected for this patient. Each isolate of these multiple episodes was characterized zymodeme MON-1.

Association between genotype and clinical manifestation

Genetic differentiation among the various populations was tested using FSTAT Version 2.9.3.2.

In France, at the end of the 1990s and early 2000s, the repellent collar had been widely use to protect dogs from parasitic transmission [21,22]. To determine whether this had an impact on genetic differentiation, we compared the isolates before and after the introduction of repel- lent collar in the AM and P endemic areas. To minimize the temporal effect on genetic variabil- ity and determine whether the repellent collar led to a bottleneck effect, the samples collected between 1996 and 2004 were excluded (Table 5). No differentiation was found in both endemic areas, thereby suggesting no bottleneck effect due to repellent collar use.

Fig 4. Temporal distribution of the 11 genotypes represented by more than four isolates.

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Nine isolates from asymptomatic carriers were compared with 11 isolates from HIV patients collected between 1994 and 1998 in the same restricted endemic area. To avoid bias, we selected isolates collected two years before and after the date of the collection of the asymptom- atic carrier isolates (1996). Unlike the findings reported by Hide et al., no genetic differentia- tion was observed between isolates from asymptomatic carriers and those derived from HIV + patients (Table 5) [9]. However, additional isolates from asymptomatic carriers are required to strengthen these findings. A genetic differentiation was observed between isolates from HIV + and VL adult patients in AM (Table 5).

Clustering analysis

Bayesian model-based analysis of the 270 isolates using STRUCTURE (with calculation of ΔK) indicated two distinct genetic populations (Fig 5A). Population A consisted of 148 samples: 73 from P, 61 from AM, seven from CO and seven from CE. This population consisted of zymo- demes MON-1 and nine isolates with zymodemes other than MON-1. Population B consisted of 109 isolates: 104 from AM, two from P, two from CO and one from CE. Isolates from Popu- lation B were all characterized zymodeme MON-1. Among the Populations A and B, 13 isolates had mixed genotypes (11 isolates corresponding to seven genotypes and two isolates corre- sponding to two genotypes in Populations A and B, respectively). The isolates with mixed genotypes shared allele characteristics of each population. All isolates with mixed genotypes were collected in the AM endemic area and were characterized zymodeme MON-1. Thus, Pop- ulation A is a mixed population with almost an equivalent number of isolates from AM and P corresponding to MON-1 and all non-MON-1 isolates. The estimated gene flow between iso- lates from AM and P within Population A (Nm value) was 8.38. Population A also displayed a marked proportion of isolates from HIV+ patients (44.7%) compared with Population B (21.6%) (p<0.05). The two populations A and B defined by STRUCTURE were significantly different as shown by the F st value 0.503 and p-value equal to 0.05. The estimated gene flow between the populations (Nm value) was 0.25, thereby indicating very few exchanges between those two populations.

The STRUCTURE analysis of Population A separately from Population B, excluding admixed isolates (13 isolates), revealed a delta K graph with two peaks at K = 4 and K = 6 (Fig 5B). The main difference between K = 4 and K = 6 was that sub-population A1’ at K = 4 was

P endemic area 11 / 12 0.0412 0.15

AM endemic area 87 / 40 0 0.95

Comparison of clinical manifestations. Other means VL, CL, MCL

AM AC vs other 1991–2001 9 / 172 0.0763 0.10000

AM AC vs HIV isolated from 1994 to 1998 in the same endemic area 11 / 9 0.0830 0.10000

HIV + vs HIV - 95 / 150 0.0683 0.05000

HIV + vs VL adult 95 / 72 0.0857 0.05000

HIV + vs CanL CatL 95 / 21 0.0167 0.50000

P HIV + vs VL adult 40 / 11 0.0020 0.80000

AM HIV + vs VL adult 52 / 50 0.1510 0.05000

IVL vs CanL CatL 58 / 21 -0.0013 0.90000

VL vs IVL 70 / 57 0.0003 0.30000

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Fig 5. Estimated population structure forL.infantumfrom Southeastern France assessed using STRUCTURE software based on the analysis of the 270L.infantumDNA samples at 12 microsatellite markers. A: The plots show the estimated membership coefficient (Q) of each isolates. Each isolate is represented by a single vertical line divided into K colors, in which K is the number of populations assumed. Each color represents one population,

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split into three populations at K = 6: sub-population A2 (four isolates from sub-population A1’), A3 (16 isolates from sub-population A1’) and A4 (15 isolates from sub-population A1’).

Whether at K = 4 or K = 6, the sub-population defined contained isolates from the AM and P endemic areas and from HIV+ patients. The non-MON-1 isolates were grouped into sub-pop- ulation A1’ and A3’ with K = 4 and into sub-population A2, A4 and A6 with K = 6. No cluster based on clinical data, geographic area or zymodeme profile was found within the defined sub- populations. Some isolates displayed mixed genotypes within the A sub-populations. At K = 4 and K = 6, 26 and 44 isolates had mixed genotypes, respectively. At K = 6, isolates with mixed genotypes came from P (n = 33; 75%), AM (n = 8; 18.2%) and CE (n = 3; 6.8%).

When excluding mixed genotypes, the sub-populations A1, A2, A3, A4, A5 and A6 as well as A1’, A2’, A3’ and A4’ were significantly different, as shown by the significant Fst values rang- ing from 0.249 to 0.833 and from 0.322 to 0.813 for K = 4 and K = 6, respectively (Table 6). At K = 4, the highest Nm value was obtained between sub-population A1’ and sub-population A3’

(0.53), whereas at K = 6, the highest Nm value was 0.75 between sub-population A2 and sub- population A6, thereby indicating only limited genotype flow between these sub-populations (Table 6).

Two main sub-populations were defined using STRUCTURE for Population B: sub-popula- tion B1 and sub-population B2. No mixed genotypes were present. Sub-population B1 con- sisted of 48 isolates from AM, two from P and one from CO. Sub-population B2 consisted of 56 isolates from AM, one from CO and one from CE. These two sub-populations were geneti- cally different as evidenced by the Fst value (0.537 and p-value = 0.05). Few exchanges occurred between these two sub-populations (Nm = 0.22 was obtained between sub-population B1 and sub-population B2).

Sub-populations A3 ’ (sub-population A K = 4) and A6 (sub-population A K = 6) displayed the highest number of alleles per population (Table 7). The expected heterozygosity (He), a measure of genetic diversity, was higher in the A sub-populations with non-MON-1 isolates compared with the A sub-populations with only MON-1 isolates (Table 7). All A sub-popula- tions displayed a high inbreeding coefficient (F

IS

) (> 0.7), whereas the sub-population B2 dis- played a low inbreeding coefficient (0.343) (Table 7).

The NJ tree presented in Fig 6 provides a graphic representation of the data. The bootstrap values based on the re-sampling of loci were low and therefore not included in the NJ tree (Fig 6). This was due to the presence of admixed genotypes and the high number of shared alleles

Table 6. Differentiation measures, migration rate and statistical significance between differentLeishmania infantumisolates according to sub- populations defined using STRUCTURE.In sub populations A, the isolates with mixed genotypes have been excluded (26 and 44 isolates for K = 4 and K = 6, respectively). Only the highest and lowestFst values are represented in this table.

Sub populations Number of Isolates Fst p-value Nm

Sub Pop A Pop A2’vs A4’ 26 / 30 0.813 0.008 0.06

K = 4 Pop A1’vs A3’ 52 / 14 0.322 0.008 0.53

Sub Pop A Pop A3 vs A5 16 / 26 0.833 0.003 0.05

K = 6 Pop A2 vs A6 7 / 13 0.249 0.003 0.75

Sub Pop B

K = 2 Pop B1 vs B2 51 / 58 0.537 0.050 0.22

Fst: degree of genetic differentiation,Nm: migration rates,p-value: statistical significance.

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even if the allelic frequencies are different between the populations and sub-populations. Two main clusters were found to correspond to the two populations obtained using STRUCTURE at K = 2. Population B formed a separate cluster from Population A. The two sub-clusters defined using STRUCTURE for Populations B1 and B2 are shown on the NJ tree. However, for Population A, the clusters defined by the NJ tree did not perfectly correlate with the A sub-pop- ulations defined using STRUCTURE for neither K = 4 nor K = 6. The sub-populations A1, A2 and A3 (A1: four genotypes from AM and seven genotypes from P; A2: one genotype from AM, one from CO and three from P; and A3: eight genotypes from AM, two from P and one from CO) are dispersed throughout the NJ tree. Within Population A, the isolates from AM and P are dispersed throughout the cluster with no correlation with endemic area, clinical form or host background. The mixed genotypes were present between the two main clusters of Pop- ulations A and B as well as within the cluster of A sub-populations. Some non-MON-1 isolates grouped together as a paraphyletic group in the sub-population A6, while the others were dis- persed among the MON-1 isolates and are present at the end of the branches. As previously described, the MON-108 isolate is closely related to the MON-1 isolates [23 – 25]. Regarding the nine isolates from AC, two (genotype 21) were present in sub-population A5, whereas seven (genotype 43) belonged to sub-population B1 and grouped with isolates from infant VL and HIV + VL patients. None of the isolates from AC has a mixed genotype. Samples isolated from CanL grouped together with human isolates, and no correlation was found between host and MLMT profile.

Discussion

Leishmaniasis due to L . infantum is endemic in Southern France. In this study, we used MLMT, a molecular tool useful for population genetic studies, to analyze an extensive set of isolates from four endemic areas in Southern France (AM, P, CE and CO). To the best of our knowledge, this study is the first to investigate a large number of L. infantum isolates from dif- ferent endemic areas in Southern France. We also focused on the AM and P endemic areas over an extended period of time. A greater number of samples came from AM than P

(AM = 178 versus P = 75) because AM is the most active foci in France with the greatest num- ber of leishmaniasis cases per year [2]. The study period was also longer for the AM area than

K = 4 Pop A2’ 26 1.500 0.052 0.013 0.763

Pop A3’ 14 5.417 0.695 0.048 0.936

Pop A4’ 30 2.000 0.161 0.014 0.917

Sub Pop A Pop A1 27 1.917 0.149 0.012 0.920

K = 6 Pop A2 7 2.417 0.395 0.071 0.843

Pop A3 16 1.917 0.169 0.016 0.913

Pop A4 15 1.917 0.184 0.006 0.972

Pop A5 26 1.500 0.052 0.013 0.763

Pop A6 13 5.000 0.680 0.051 0.931

Sub Pop B Pop B1 51 1.500 0.080 0.011 0.860

K = 2 Pop B2 58 1.917 0.067 0.0445 0.34337

In sub populations A, the isolates with mixed genotypes have been excluded (26 and 44 isolates for K = 4 and K = 6, respectively). n: number of isolates per population;Na: number of alleles;Ho: observed heterozygosity;He: expected heterozygosity;FIS: inbreeding coefficient.

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for the P endemic area (AM: 1978–2011; P: 1993–2009). This aspect may generate a sampling bias, although no significant genetic differentiation was found when comparing isolates from AM and P during the same time period. Although MON-1 is the most prevalent zymodeme, other zymodemes also circulate in the south of France [7]. Microsatellite characterization of L . infantum isolates revealed a total of 121 different genotypes. Overall, 91 unique genotypes and 30 repeated genotypes were found. A greater number of repeated genotypes were observed in AM compared with P for the same period, thereby suggesting variations in the transmission cycle between the two areas such as outbreak, vector diversity or density, or host density.

In the AM endemic area, the isolates belonged to two main populations as defined by STRUCTURE: Population A and Population B. Within Population A, gene flow occurred between the AM and P endemic areas. The spread of isolates seems to be from AM to P, as indicated by the results of genotype 21, which was found 15 years later in P.

Substantial genetic diversity was found to be comparable to other endemic areas, even within zymodeme MON-1, thereby confirming previous analyses assessed by other markers [26]. As genetic differentiation depends on the area, our findings suggest strong epidemiologi- cal structuring. This is in agreement with the known mechanism of Leishmania transmission and spread in micro-foci and the entomologic data that have demonstrated limited sandfly dis- persion [27 – 31]. Indeed, considering the behavior of the phlebotomine sandfly, it seems less likely that the spread of isolates from AM to P is due to sandfly movement [32]. Unfortunately, due to the small sample size of the phlebotomine sandfly isolates, we cannot investigate the transmission between sandflies, humans and canine hosts in further detail. We suspect that people traveling with their infected dogs between the endemic areas plays a possible role in the etiology of these exchanges. This has been already described for the emergence of L. infantum in South America probably via Conquistadores infected dogs from Portugal [33]. More recently, an intercontinental transportation from France to French Guiana was also reported due to the probable importation of L . infantum from an infected dog [34]. Notably, some repeated genotypes in the AM endemic area are well settled and continue to spread through the area over time. Indeed, some repeated genotypes were detected during a limited period, ranging from 6 to 15 years, and are no longer detected (genotypes 36, 43, 46, 53, 68 and 77).

However, other genotypes were still detected in 2011 (genotypes 34, 55 and 57) and one geno- type spread to P endemic area (genotype 21). The mixed genotypes between Population A and Population B were isolated in the AM endemic area, whereas in the A sub-populations, 75% of the mixed genotypes came from the P endemic area. We also observed a predominance of iso- lates from HIV+ patients in Population A (44.7%) compared with Population B (21.6%), which may indicate a variation in virulence. Indeed, these isolates from HIV+ patients may produce leishmaniasis in immunocompromised patients, whereas affected immunocompetent patients may develop only an asymptomatic infection [35]. This hypothesis is in agreement with the distribution of isolates from AC in both Population A and Population B. These isolates belonged to the genotypes 21 (2 AC) and 43 (7 AC), with samples from HIV+ VL, IVL, VL and CanL cases and samples from infant VL and HIV+ VL patients, respectively. The comparison of isolates from AC and those from HIV+ patients isolated during the same period and within

ovals at K = 6 for A sub-populations and K = 2 for B sub-populations. The isolates with no color are those with mixed genotypes within A sub-populations at K = 6. MEGA 4 software was used to visualize the neighbor-joining tree.

doi:10.1371/journal.pntd.0004303.g006

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well as all endemic foci of leishmaniasis), where the isolates responsible for leishmaniasis repre- sent only the tip of the iceberg [36]. Indeed, depending on the test used to detect asymptomatic carriage, prevalence varies from 30% to 46.8% in the AM endemic area [36]. Although our study provides important insight into leishmaniasis epidemiology in AM and P, our panel rep- resents only a small proportion of the L . infantum population circulating in Southern France as samples from asymptomatic carriers, dogs and sandflies are underrepresented.

Microsatellite analyses may be useful to estimate relapse and re-infection rates, which is important to evaluate anti-Leishmania drug efficacy and transmission dynamics, respectively.

This aspect is particularly important for the follow-up of patient treatment. MLMT may also be a useful tool to differentiate between relapses from re-infection cases [11,25,26,35,37,38].

Moreover, Bourgeois et al. have described “ active chronic visceral leishmaniasis ” in patients with several episodes of VL [20]. In this particular form of the disease, identifying the MLMT profile of each isolate responsible of each episode of VL could be useful to monitor and opti- mize treatment regimes. In our study, we detected probable treatment failure in HIV+ and non-HIV patients, as the MLMT profiles were indistinguishable from one episode to another.

Certain patients likely experienced re-infection, as isolates from two different episodes of leish- maniasis in same patient displayed different MLMT profiles. However, we cannot exclude the possibility of a mixed infection with differential strain isolation depending on the time of sam- pling. Due to the small number of patients with isolates from several biological samples at dif- ferent times, the rate of relapse and re-infection needs to be confirmed on a larger sample set.

Thus, the results on relapse and re-infection should be interpreted with caution. Further inves- tigations are required to assess these hypotheses in further detail.

The high ratio of repeated genotypes in HIV patients (81.6%) compared with the remaining population (41%) may be due to an outbreak amongst this fragile human population. Out- breaks have already been reported among intravenous drug users, a population also frequently affected by HIV infection [39,40]. Nevertheless, we have no information concerning this aspect of the case population in our study.

Faucher et al. have highlighted the heterogeneity of environments associated with VL trans- mission in Southeastern France [5]. The authors showed two distinct foci strongly associated with specific environments. One focus, corresponding to the AM endemic area, was character- ized by scattered habitation and mixed forest in the foothills. In contrast, the other focus in the P endemic area was centered in urban areas of Marseille. These environmental differences cor- relate with the strong genetic differentiation we found between the Leishmania populations from AM and P. Indeed, the ecosystem influences the transmission cycle and thus the popula- tion dynamics of parasites. Moreover, in the P endemic area, Toscana virus, which is responsi- ble for summer meningitis, and L. infantum share the same vector, Phlebotomus perniciosus. A recent study has described dogs co-infected by these two organisms [41]. Although cases of co- infection in humans or vectors have not been reported, we suspect that is also possible. This phenomenon of co-infection may have an impact on Leishmania transmission and should be addressed in future studies to understand whether this may also influence parasite evolution.

Other wild reservoirs of L . infantum have been demonstrated in Europe such as fox, rats

and hare [42]. These wild reservoirs are able to transmit L. infantum to sandflies. However, the

isolates from wild reservoirs have indistinguishable genotypes from those derived from domes-

tic dogs and humans [26,43]. No isolates from wild animals were included in our study. The

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with our data which is probably due to the high number of strains with mixed genotypes.

Indeed the nine non-MON-1 isolates did not group into a separate population but rather clus- tered into Population A with a majority of the MON-1 isolates. In the NJ tree, some non- MON-1 isolates appeared as a paraphyletic group, while others were either isolated or dis- persed among other zymodemes [23 – 25]. The zymodeme MON-108 (genotype 92) isolate appeared very close to MON-1 isolates with the genotype 37 [23–25].

In our study, no correlation was found between MLMT profile, clinical expression of the disease, immune status and host. Finally, MLMT is more discriminant and thus more appro- priate than MLEE to evaluate epidemiological changes among parasite population in Southern France. MLMT data provided a better understanding of gene flow between L. infantum popula- tions within the Southeastern France endemic area.

Supporting Information

S1 Table. Designation, characteristics and MLMT profiles of the Leishmania infantum iso- lates used in this study. AM: Alpes-Maritimes; P: Provence; CE: Cévennes; CO: Corsica. VL – Visceral leishmaniasis; IVL–Infant under 15 years visceral leishmaniasis; CL–Cutaneous leish- maniasis; MCL – Muco-cutaneous leishmaniasis; RVL — New episode of leishmaniasis in patients; AC–Asymptomatic carrier; CanL–Canine leishmaniasis; CatL–Leishmaniasis in cat;

PHLE: isolate from phlebotomine sandfly; UK – Unknown. n. d. = not defined.

(XLS)

Acknowledgments

We thank Mohammad Akhoundi for his precious assistance. The data used in this study were processed at the GenSeq capillary electrophoresis facilities of the labex « Centre Méditerranéen de l ’ Environnement et de la Biodiversité », Montpellier.

Author Contributions

Conceived and designed the experiments: CP PM ALB EL RP MH. Performed the experiments:

CP ALB FP FJ SM GM SA MH. Analyzed the data: CP ALB FP FJ SM GM SA RP MH. Con- tributed reagents/materials/analysis tools: CP PM ALB EL FP BF FJ SM GM SA RP MH.

Wrote the paper: CP PM ALB EL FP FJ SM RP MH.

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